Development of an online implementation intervention for aphasia clinicians to increase the intensity and comprehensiveness of their service
Bibliographic record
Abstract
To describe the process and outcome of a user and theory informed online intervention for speech pathologists targeting the implementation of intensive and comprehensive aphasia services. The design process followed the eight steps outlined by the Behaviour Change Wheel and incorporated the principles of Integrated Knowledge Translation (IKT). Eight speech pathology researchers and clinicians from four countries (Australia, Canada, the United Kingdom and Ireland) contributed to three focus groups via videoconference. The online platform, Aphasia Nexus: Connecting Evidence to Practice, provides resources, guidance and support for speech pathologists seeking to improve the intensity and comprehensiveness of their aphasia service. A collaborative and iterative design process facilitated the creation of an intervention envisioned by participants. The website contains both interactive elements and resource links which have been arranged under the three headings of resources, action and support. The inclusion of multi-national researchers and clinicians benefitted a design process to make implementation more likely.IMPLICATIONS FOR REHABILITATIONTheoretically informed implementation interventions aim to change the everyday clinical practice of health workers.An online platform has been developed to support speech pathologists’ implementation of intensive and comprehensive aphasia services.A collaborative design process can be beneficial in creating an intervention that is relevant to research-users and is more likely to be implemented. Theoretically informed implementation interventions aim to change the everyday clinical practice of health workers. An online platform has been developed to support speech pathologists’ implementation of intensive and comprehensive aphasia services. A collaborative design process can be beneficial in creating an intervention that is relevant to research-users and is more likely to be implemented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".